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cs.LG2026
Attribution-Guided Continual Learning for Large Language Models
Yazheng Liu, Yuxuan Wan, Rui Xu +3
Large language models (LLMs) often suffer from catastrophic forgetting in continual learning: after learning new tasks sequentially, they perform worse on earlier tasks. Existing m…
cs.LG2025
Group Fairness Meets the Black Box: Enabling Fair Algorithms on Closed LLMs via Post-Processing
Ruicheng Xian, Yuxuan Wan, Han Zhao
Instruction fine-tuned large language models (LLMs) enable a simple zero-shot or few-shot prompting paradigm, also known as in-context learning, for building prediction models. Thi…